Benchmarking Geometric Morphometric Methods: A Performance Evaluation for Gastropod Shell Shape Analyses

Understanding morphological variation is crucial for the study of speciation and for conservation as it helps in assessing biodiversity and predicting responses to environmental changes. These approaches are broadly applicable but are especially valuable in marine environments, where species are often elusive, difficult to study, and face heightened threats from rapid environmental shifts. The marine snail Littorina saxatilis is notable for its extensive polymorphism in shell shape, size, and colour, with ecotypes that evolve in response to environmental forces including wave exposure and crab predation. Morphometric tools have been central to investigating the mechanisms driving this phenotypic divergence; yet, a direct comparison of their methodological efficacy is lacking. Here, we took advantage of L. saxatilis ecotypes to contrast three morphometric approaches: elliptical Fourier analysis (EFA), landmarks-based geometric morphometrics (GM), and the growth-based model implemented in the ShellShaper software (SS). We assessed their clustering power, biological interpretability, robustness to measurement error and transferability among datasets. Our findings provide insights to guide method selection in studies aimed at exploring morphological variation: EFA is better suited for high-throughput screening and describing intermediate shapes; SS offers superior clustering power with highly interpretable growth parameters; and GM is best for detailed anatomical studies but is less efficient for large datasets. We provide guidelines to align method selection with specific research goals, balancing analytical efficiency with the required morphological and biological insight. By following this framework, researchers can ensure that robust morphological analysis is achieved, which is essential not only for elucidating mechanisms of adaptation and speciation but also for effective management and conservation of marine biodiversity.